Clustering of the White Matter Tracts in the Rat Spinal Cord Based on Quantitative Histology

Résumé La matière blanche de la moelle épinière est vraiment importante pour la transmission de l’information entre le corps et le cerveau et vice-versa. La matière blanche est divisée entre différents faisceaux (tracts) dépendamment de la fonctionnalité de chaque faisceau. Dans les pathologies qui affectent la moelle épinière, c’est normalement les faisceaux de la matière blanche qui sont les plus affectées. Comprendre comment les faisceaux sont divisés est donc important pour mettre en place une méthodologie qui peut facilement identifier les faisceaux sains et les comparer avec ceux qui sont pathologiques. Présentement, les techniques utilisées pour déterminer les faisceaux de la matière blanche sont des techniques relativement anciennes qui utilisent différents types des colorants pour identifier différents types de cellules. Les atlas de matière blanche étaient créés par la suite visuellement en se basant sur ces colorants. En plus, l’atlas était souvent créé sur un seul échantillon (e.g. un rat), ainsi, même avec plusieurs colorants, il n’était pas possible de visualiser tous les faisceaux. Le but de ce projet était justement de créer une méthodologie qui permet de visualiser tous les faisceaux de la matière blanche en combinant une haute résolution en histologie quantitative et un algorithme de regroupement. On a appliqué trois types d’algorithmes de regroupement: l’agglomerative clustering, le k-means clustering et le spectral clustering. On a aussi validé les trois algorithmes visuellement en comparant la position des faisceaux avec les anciens atlas et aussi quantitativement avec la silhouette score et le davies-bouldin score. L’algorithme de l’agglomerative clustering a permis d’identifier des faisceaux similaires à ceux de l’ancien atlas de Paxinos pour le rat que les deux autres algorithmes de regroupement. Par contre, en utilisant les méthodes de validation quantitative, on a constaté que le spectral clustering a un meilleur score (0.43 silhouette et 0.85 davies-bouldin) que les deux autres algorithmes. On peut voir cependant que les clusters de l’agglomerative clustering semble donner de meilleur résultat et plus stable que les deux autres algorithmes. En particulier, on a pu identifier des faisceaux que le paxinos atlas de rat ne comprend pas. En conclusion, on a vu que le fait d’appliquer un algorithme de regroupement sur des données quantitatives d’histologie a donné des résultats comparables avec ce qui est déjà dans la littérature. On pouvait alors essayer d’implémenter ça sur d’autres espèces et sur des données pathologiques pour voir comment les pathologies affectent les faisceauxs de la matière blanche.----------ABSTRACT The white matter tracts in the spinal cord make up the entire cytoarchitecture of how information travels from the body to the brain and vice-versa. It is usually the white matter tracts that are the target of pathologies and thus would impact all the various functions of the body from motor control to loss of organ function. It is therefore quite important to understand how the tracts are grouped and to develop more easily available and simple to use techniques to do so. The methods at this point in time that have been used to characterize the white matter tracts have all been done using manual staining techniques and visual delineation of the tracts based off of these stains. Furthermore, specifically for the rat atlas, the gold standard was done using only a single specimen. Moreover, they were still unable to visualize all of the tracts that based off of the literature are supposed to be there. Therefore, we have developed a pipeline to be able to visualize the tracts of the white matter based solely on high resolution quantitative histology using only one stain to visualize the myelin sheath from which then we can obtain various metric maps such as the axon diameter and density as well as myelin thickness. We applied three clustering algorithms on the averaged metric maps of the 5 rats to visualize the best results for the clustering and then validated them quantitatively. The algorithms we tested were agglomerative clustering, k-means clustering and spectral clustering along with the validation methods of silhouette score and davies-bouldin score. Based on the visual comparison between the results and the gold standard atlases currently in use, agglomerative clustering seemed to have a more representative output in comparison. The clusters also seemed more stable for agglomerative clustering compared to the other two techniques. However, based on the quantitative validation, the silhouette score was higher for spectral clustering (0.43) versus 0.38 and 0.37 for agglomerative clustering and k-means clustering respectively. The davies-bouldin score was better for spectral and k-means clustering (0.85 and 0.87) whereas for agglomerative clustering a score of 2.68 was obtained. All things taken into account however, it would seem that agglomerative clustering with the use of a connectivity matrix gives the most stable and comparable results. Thus, we were able to implement a pipeline using quantitative metrics as the sole inputs to obtain very similar results to the gold standard atlases with an applied clustering algorithm. We can therefore apply this pipeline on other species to investigate the placement of the white matter tracts as well as implement it on pathological data to see how pathologies would affect the white matter tracts

A quantitative comparison of dispersed spore/pollen and plant megafossil assemblages from a Middle Jurassic plant bed from Yorkshire, UK

Detailed quantitative data has previously been collected from plant megafossil assemblages from a Middle Jurassic (Aalenian) plant bed from Hasty Bank, North Yorkshire, UK. We conducted a similar analysis of palynological dispersed sporomorph (spore and pollen) assemblages collected from the same section using the same sampling regime: 67 sporomorph taxa were recorded from 50 samples taken at 10 cm intervals through the plant bed. Basic palynofacies analysis was also undertaken on each sample. Both dispersed sporomorph and plant megafossil assemblages display consistent changes in composition, diversity (richness), and abundance through time. However, the dispersed sporomorph and plant megafossil records provide conflicting evidence for the nature of parent vegetation. Specifically, conifers and ferns are underrepresented in plant megafossil assemblages, bryophytes and lycopsids are represented only in sporomorph assemblages, and sphenophytes, pteridosperms, Caytoniales, Cycadales, Ginkgoales and Bennettitales are comparatively underrepresented in sporomorph assemblages. Combined multivariate analysis (correspondence analysis and nonmetric multidimensional scaling) of sporomorph occurrence/abundance data demonstrates that temporal variation in sporomorph assemblages is the result of depositional change through the plant bed. The reproductive strategies of parent plants are considered to be a principal factor in shaping many of the major abundance and diversity irregularities between dispersed sporomorph and plant megafossil data sets that seemingly reflects different parent vegetation. Preferential occurrence/preservation of sporomorphs and equivalent parent plants is a consequence of a complex array of biological, ecological, geographical, taphonomic, and depositional factors that act inconsistently between and within fossil assemblages, which results in notable discrepancies between data sets

Study on a model of street vended food choices by Korean high school students

Street vended food (SVF) includes food and beverages prepared and sold outdoors or in public areas by street merchants for consumption on the scene or later without further preparation. Due to its low price and convenience, SVF has been popular in Korea for a long time, particularly with high school students. Beyond Korea, SVF is also popular in southeast Asia and southern Africa in the form of ready-to-eat food. This study on high school students, who are main consumers of SVF in Korea, focused on the factors that affect consumer loyalty. The study was performed by questionnaire and used AMOS software to develop a structural equation model. The results of verifying the model's fidelity were χ2 = 685.989, df = 261, GFI = 0.851, AGFI = 0.814, NFI = 0.901, CFI = 0.907, RMR = 0.048, indicating a satisfying structural model. SVF quality and service, emotional response, and the physical environment had a statistically significant effect on consumer loyalty. In contrast, SVF sanitation had no statistically significant effect on consumer loyalty. Based on these results, the sanitary management of SVF needs to be addressed immediately combined with education for SVF providers to maintain a clean environment

Histology-informed automatic parcellation of white matter tracts in the rat spinal cord

The white matter is organized into “tracts” or “bundles,” which connect different parts of the central nervous system. Knowing where these tracts are located in each individual is important for understanding the cause of potential sensorial, motor or cognitive deficits and for developing appropriate treatments. Traditionally, tracts are found using tracer injection, which is a difficult, slow and poorly scalable technique. However, axon populations from a given tract exhibit specific characteristics in terms of morphometrics and myelination. Hence, the delineation of tracts could, in principle, be done based on their morphometry. The objective of this study was to generate automatic parcellation of the rat spinal white matter tracts using the manifold information from scanning electron microscopy images of the entire spinal cord. The axon morphometrics (axon density, axon diameter, myelin thickness and g-ratio) were computed pixelwise following automatic axon segmentation using AxonSeg. The parcellation was based on an agglomerative clustering algorithm to group the tracts. Results show that axon morphometrics provide sufficient information to automatically identify some white matter tracts in the spinal cord, however, not all tracts were correctly identified. Future developments of microstructure quantitative MRI even bring hope for a personalized clustering of white matter tracts in each individual patient. The generated atlas and the associated code can be found at https://github.com/neuropoly/tract-clustering

Data_Sheet_1_Histology-informed automatic parcellation of white matter tracts in the rat spinal cord.PDF

The white matter is organized into “tracts” or “bundles,” which connect different parts of the central nervous system. Knowing where these tracts are located in each individual is important for understanding the cause of potential sensorial, motor or cognitive deficits and for developing appropriate treatments. Traditionally, tracts are found using tracer injection, which is a difficult, slow and poorly scalable technique. However, axon populations from a given tract exhibit specific characteristics in terms of morphometrics and myelination. Hence, the delineation of tracts could, in principle, be done based on their morphometry. The objective of this study was to generate automatic parcellation of the rat spinal white matter tracts using the manifold information from scanning electron microscopy images of the entire spinal cord. The axon morphometrics (axon density, axon diameter, myelin thickness and g-ratio) were computed pixelwise following automatic axon segmentation using AxonSeg. The parcellation was based on an agglomerative clustering algorithm to group the tracts. Results show that axon morphometrics provide sufficient information to automatically identify some white matter tracts in the spinal cord, however, not all tracts were correctly identified. Future developments of microstructure quantitative MRI even bring hope for a personalized clustering of white matter tracts in each individual patient. The generated atlas and the associated code can be found at https://github.com/neuropoly/tract-clustering.</p

Effect of stimulant medication on loss of control eating in youth with attention deficit/hyperactivity disorder: a prospective, observational case series study protocol.

BACKGROUND: Loss of control eating (LOC-E) in youth predicts the later development of full-syndrome binge-eating disorder (BED), and therefore, could be a relevant target for prevention treatments. To develop these treatments, it is important to understand the underlying disease processes and mechanisms. Based on the putative role of neurocognitive impairments in the pathogenesis of LOC-E, treatments that modulate these neurocognitive factors warrant further exploration. For instance, stimulants are an effective treatment for impulsivity in youth with attention deficit/hyperactivity disorder (ADHD) and have been shown to improve symptoms of BED in adults. Notably, stimulants have not been examined as a treatment for LOC-E in youth. To explore this gap, we aim to measure change in LOC-E episodes and secondary outcomes in youth with comorbid ADHD and LOC-E who are being started on stimulants. METHODS: We will collect prospective observational data on forty 8-to-13-year-old youth diagnosed with comorbid ADHD and LOC-E who are initiating a stimulant for ADHD. Prior to stimulant initiation, participants will complete baseline measures including LOC-E episode frequency in the last 3 months (primary outcome), and secondary outcomes including disordered eating cognitions, emotions and behaviors, ADHD symptom severity, parental LOC-E, impulsivity and reward sensitivity, and anxiety/mood severity. Outcome measurements will be gathered again at 3-months after initiating the stimulant. Within-patient standardized effect sizes with 95% confidence intervals will be calculated from baseline to 3-month follow-up for all outcomes. DISCUSSION: Many individuals with LOC-E or binge eating do not fully remit over the course of psychotherapy. Whereas psychotherapy may address psychological and sociocultural domains associated with LOC-E, some individuals with neurocognitive impairments (e.g., ADHD) and neurobiological deficits (e.g., low intrasynaptic dopamine or norepinephrine) may benefit from adjunctive treatment that targets those factors. This will be the first study to provide pilot data for future studies that could examine both the effect of stimulants on LOC-E in youth and underlying mechanisms. TRIAL REGISTRATION: Trial registration number: NCT05592119

White Matter Microscopy Database

The purpose of this repository is to provide a freely-accessible and curated microscopy data of white matter axons from the central and peripheral nervous system. This repository can be used for: - Training/Testing automatic methods for segmenting white matter microstructure - Documenting white matter microstructure across various species - Validating quantitative MRI methods (e.g., diffusion, magnetization transfer, etc.). For more information about this project, please see this presentation: https://docs.google.com/presentation/d/1Ww8YaanjQ1tWNyL4AswHtgqDtkkCSVV8TnXkYqkRM5A/edit?usp=sharing For more information about data organization please visit our wiki page: https://osf.io/yp4qg/wiki/home/ CITATION: For general citation, please refer to the box "Citation" on this page. If you use specific datasets, please also mention the authors of the dataset that you will find in the json file. HOW TO UPLOAD DATA: If you would like to add images to this project, please email Julien Cohen-Adad ([email protected]